Overview

Dataset statistics

Number of variables21
Number of observations500
Missing cells143
Missing cells (%)1.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory82.2 KiB
Average record size in memory168.3 B

Variable types

Numeric18
Categorical3

Alerts

Unnamed: 0 is highly overall correlated with 회원번호High correlation
회원번호 is highly overall correlated with Unnamed: 0High correlation
구매금액(clean) is highly overall correlated with 구매수량(clean) and 2 other fieldsHigh correlation
구매수량(clean) is highly overall correlated with 구매금액(clean) and 2 other fieldsHigh correlation
총방문횟수 is highly overall correlated with 구매금액(clean) and 2 other fieldsHigh correlation
1회방문시평균구매금액 is highly overall correlated with 구매금액(clean) and 2 other fieldsHigh correlation
회원상태 is highly imbalanced (89.4%)Imbalance
성별 is highly imbalanced (63.3%)Imbalance
결혼유무 has 139 (27.8%) missing valuesMissing
Unnamed: 0 is uniformly distributedUniform
회원번호 is uniformly distributedUniform
Unnamed: 0 has unique valuesUnique
회원번호 has unique valuesUnique
구매금액(clean) has unique valuesUnique
1회방문시평균구매금액 has unique valuesUnique
간식(%) has 19 (3.8%) zerosZeros
건강(%) has 165 (33.0%) zerosZeros
과실(%) has 63 (12.6%) zerosZeros
생활용품(%) has 59 (11.8%) zerosZeros
서류(%) has 68 (13.6%) zerosZeros
수산(%) has 18 (3.6%) zerosZeros
양념/가루(%) has 37 (7.4%) zerosZeros
음료(%) has 60 (12.0%) zerosZeros
잡곡(%) has 103 (20.6%) zerosZeros
주곡(%) has 109 (21.8%) zerosZeros
채소(%) has 9 (1.8%) zerosZeros
축산물(%) has 9 (1.8%) zerosZeros

Reproduction

Analysis started2022-12-27 10:22:03.069482
Analysis finished2022-12-27 10:22:30.632005
Duration27.56 seconds
Software versionpandas-profiling vv3.6.1
Download configurationconfig.json

Variables

Unnamed: 0
Real number (ℝ)

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.5
Minimum0
Maximum499
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:30.696719image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile24.95
Q1124.75
median249.5
Q3374.25
95-th percentile474.05
Maximum499
Range499
Interquartile range (IQR)249.5

Descriptive statistics

Standard deviation144.48183
Coefficient of variation (CV)0.5790855
Kurtosis-1.2
Mean249.5
Median Absolute Deviation (MAD)125
Skewness0
Sum124750
Variance20875
MonotonicityStrictly increasing
2022-12-27T19:22:30.796644image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
0.2%
329 1
 
0.2%
342 1
 
0.2%
341 1
 
0.2%
340 1
 
0.2%
339 1
 
0.2%
338 1
 
0.2%
337 1
 
0.2%
336 1
 
0.2%
335 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
0 1
0.2%
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
ValueCountFrequency (%)
499 1
0.2%
498 1
0.2%
497 1
0.2%
496 1
0.2%
495 1
0.2%
494 1
0.2%
493 1
0.2%
492 1
0.2%
491 1
0.2%
490 1
0.2%

회원번호
Real number (ℝ)

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2381.396
Minimum2101
Maximum2660
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:30.891383image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2101
5-th percentile2125.95
Q12240.75
median2383.5
Q32523.25
95-th percentile2632.05
Maximum2660
Range559
Interquartile range (IQR)282.5

Descriptive statistics

Standard deviation163.29497
Coefficient of variation (CV)0.068571109
Kurtosis-1.21892
Mean2381.396
Median Absolute Deviation (MAD)142
Skewness-0.02665163
Sum1190698
Variance26665.246
MonotonicityStrictly increasing
2022-12-27T19:22:30.981076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2101 1
 
0.2%
2474 1
 
0.2%
2490 1
 
0.2%
2488 1
 
0.2%
2487 1
 
0.2%
2486 1
 
0.2%
2485 1
 
0.2%
2484 1
 
0.2%
2483 1
 
0.2%
2482 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
2101 1
0.2%
2102 1
0.2%
2103 1
0.2%
2104 1
0.2%
2105 1
0.2%
2106 1
0.2%
2107 1
0.2%
2108 1
0.2%
2109 1
0.2%
2110 1
0.2%
ValueCountFrequency (%)
2660 1
0.2%
2659 1
0.2%
2656 1
0.2%
2655 1
0.2%
2653 1
0.2%
2652 1
0.2%
2651 1
0.2%
2650 1
0.2%
2649 1
0.2%
2648 1
0.2%

회원상태
Categorical

Distinct2
Distinct (%)0.4%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
정상회원
492 
탈퇴
 
7

Length

Max length4
Median length4
Mean length3.9719439
Min length2

Characters and Unicode

Total characters1982
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정상회원
2nd row정상회원
3rd row정상회원
4th row정상회원
5th row정상회원

Common Values

ValueCountFrequency (%)
정상회원 492
98.4%
탈퇴 7
 
1.4%
(Missing) 1
 
0.2%

Length

2022-12-27T19:22:31.069596image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-27T19:22:31.143411image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
정상회원 492
98.6%
탈퇴 7
 
1.4%

Most occurring characters

ValueCountFrequency (%)
492
24.8%
492
24.8%
492
24.8%
492
24.8%
7
 
0.4%
7
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1982
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
492
24.8%
492
24.8%
492
24.8%
492
24.8%
7
 
0.4%
7
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1982
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
492
24.8%
492
24.8%
492
24.8%
492
24.8%
7
 
0.4%
7
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1982
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
492
24.8%
492
24.8%
492
24.8%
492
24.8%
7
 
0.4%
7
 
0.4%

성별
Categorical

Distinct2
Distinct (%)0.4%
Missing3
Missing (%)0.6%
Memory size4.0 KiB
462 
 
35

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters497
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
462
92.4%
35
 
7.0%
(Missing) 3
 
0.6%

Length

2022-12-27T19:22:31.200046image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-27T19:22:31.265541image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
462
93.0%
35
 
7.0%

Most occurring characters

ValueCountFrequency (%)
462
93.0%
35
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 497
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
462
93.0%
35
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 497
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
462
93.0%
35
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 497
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
462
93.0%
35
 
7.0%

결혼유무
Categorical

Distinct2
Distinct (%)0.6%
Missing139
Missing (%)27.8%
Memory size4.0 KiB
미혼
194 
기혼
167 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters722
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기혼
2nd row기혼
3rd row기혼
4th row기혼
5th row기혼

Common Values

ValueCountFrequency (%)
미혼 194
38.8%
기혼 167
33.4%
(Missing) 139
27.8%

Length

2022-12-27T19:22:31.322720image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2022-12-27T19:22:31.397848image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
미혼 194
53.7%
기혼 167
46.3%

Most occurring characters

ValueCountFrequency (%)
361
50.0%
194
26.9%
167
23.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 722
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
361
50.0%
194
26.9%
167
23.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 722
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
361
50.0%
194
26.9%
167
23.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 722
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
361
50.0%
194
26.9%
167
23.1%

구매금액(clean)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3723115.5
Minimum6100
Maximum22346350
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:31.475214image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum6100
5-th percentile139470
Q1797285
median2515165
Q35418397.5
95-th percentile11085077
Maximum22346350
Range22340250
Interquartile range (IQR)4621112.5

Descriptive statistics

Standard deviation3869142.2
Coefficient of variation (CV)1.0392216
Kurtosis4.1196975
Mean3723115.5
Median Absolute Deviation (MAD)1953750
Skewness1.8139171
Sum1.8615578 × 109
Variance1.4970261 × 1013
MonotonicityNot monotonic
2022-12-27T19:22:31.566520image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1991230 1
 
0.2%
5380155 1
 
0.2%
770010 1
 
0.2%
3841340 1
 
0.2%
2809280 1
 
0.2%
94750 1
 
0.2%
186000 1
 
0.2%
2694100 1
 
0.2%
11853005 1
 
0.2%
335590 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
6100 1
0.2%
10800 1
0.2%
33700 1
0.2%
34900 1
0.2%
38900 1
0.2%
39100 1
0.2%
47050 1
0.2%
54200 1
0.2%
57000 1
0.2%
62900 1
0.2%
ValueCountFrequency (%)
22346350 1
0.2%
21950630 1
0.2%
20191005 1
0.2%
19893210 1
0.2%
19646542 1
0.2%
18681595 1
0.2%
17307425 1
0.2%
17170370 1
0.2%
16268250 1
0.2%
15302800 1
0.2%

구매수량(clean)
Real number (ℝ)

Distinct464
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean766.44856
Minimum2
Maximum4459.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:31.663131image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile28.85
Q1165
median517.25
Q31089.9
95-th percentile2281.437
Maximum4459.4
Range4457.4
Interquartile range (IQR)924.9

Descriptive statistics

Standard deviation793.62272
Coefficient of variation (CV)1.0354546
Kurtosis3.9252209
Mean766.44856
Median Absolute Deviation (MAD)396.75
Skewness1.8023819
Sum383224.28
Variance629837.02
MonotonicityNot monotonic
2022-12-27T19:22:31.754585image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99 3
 
0.6%
104 3
 
0.6%
84 3
 
0.6%
145 3
 
0.6%
54 3
 
0.6%
165 3
 
0.6%
22 3
 
0.6%
2 3
 
0.6%
381 2
 
0.4%
29 2
 
0.4%
Other values (454) 472
94.4%
ValueCountFrequency (%)
2 3
0.6%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
7 1
 
0.2%
7.5 1
 
0.2%
8 1
 
0.2%
12 2
0.4%
16 1
 
0.2%
17 1
 
0.2%
ValueCountFrequency (%)
4459.4 1
0.2%
4425.7 1
0.2%
4373.6 1
0.2%
4044.2 1
0.2%
3870.15 1
0.2%
3566.35 1
0.2%
3539.3 1
0.2%
3430.3 1
0.2%
3298.4 1
0.2%
3295.8 1
0.2%

총방문횟수
Real number (ℝ)

Distinct169
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.09
Minimum1
Maximum176
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:31.848660image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q131
median70
Q3118
95-th percentile160
Maximum176
Range175
Interquartile range (IQR)87

Descriptive statistics

Standard deviation50.302312
Coefficient of variation (CV)0.66108965
Kurtosis-1.1410299
Mean76.09
Median Absolute Deviation (MAD)42
Skewness0.27064686
Sum38045
Variance2530.3225
MonotonicityNot monotonic
2022-12-27T19:22:32.059997image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 9
 
1.8%
2 8
 
1.6%
19 8
 
1.6%
82 8
 
1.6%
28 8
 
1.6%
34 7
 
1.4%
68 7
 
1.4%
89 6
 
1.2%
15 6
 
1.2%
123 6
 
1.2%
Other values (159) 427
85.4%
ValueCountFrequency (%)
1 5
1.0%
2 8
1.6%
3 3
 
0.6%
4 5
1.0%
5 5
1.0%
6 2
 
0.4%
7 2
 
0.4%
8 5
1.0%
9 1
 
0.2%
10 4
0.8%
ValueCountFrequency (%)
176 1
0.2%
175 1
0.2%
174 1
0.2%
173 2
0.4%
172 2
0.4%
171 2
0.4%
170 1
0.2%
169 2
0.4%
168 2
0.4%
167 2
0.4%

간식(%)
Real number (ℝ)

Distinct475
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15217304
Minimum0
Maximum0.51783944
Zeros19
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:32.155839image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.017464328
Q10.097763792
median0.1465516
Q30.19187246
95-th percentile0.30775338
Maximum0.51783944
Range0.51783944
Interquartile range (IQR)0.094108666

Descriptive statistics

Standard deviation0.087334852
Coefficient of variation (CV)0.57391805
Kurtosis2.2673782
Mean0.15217304
Median Absolute Deviation (MAD)0.046246918
Skewness0.99043297
Sum76.086518
Variance0.0076273763
MonotonicityNot monotonic
2022-12-27T19:22:32.252996image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19
 
3.8%
0.3333333333 3
 
0.6%
0.2 2
 
0.4%
0.1538461538 2
 
0.4%
0.1161290323 2
 
0.4%
0.09090909091 2
 
0.4%
0.4 2
 
0.4%
0.1132245213 1
 
0.2%
0.1528689695 1
 
0.2%
0.2592592593 1
 
0.2%
Other values (465) 465
93.0%
ValueCountFrequency (%)
0 19
3.8%
0.009615384615 1
 
0.2%
0.009708737864 1
 
0.2%
0.01170446233 1
 
0.2%
0.01333333333 1
 
0.2%
0.01379310345 1
 
0.2%
0.01470588235 1
 
0.2%
0.01760950913 1
 
0.2%
0.0202020202 1
 
0.2%
0.02169197397 1
 
0.2%
ValueCountFrequency (%)
0.517839445 1
0.2%
0.5017761989 1
0.2%
0.4880952381 1
0.2%
0.4825291181 1
0.2%
0.4693877551 1
0.2%
0.462962963 1
0.2%
0.4455958549 1
0.2%
0.4336708426 1
0.2%
0.4086538462 1
0.2%
0.404290429 1
0.2%

건강(%)
Real number (ℝ)

Distinct335
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0098402206
Minimum0
Maximum1
Zeros165
Zeros (%)33.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:32.349089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0033832402
Q30.0083608985
95-th percentile0.025600231
Maximum1
Range1
Interquartile range (IQR)0.0083608985

Descriptive statistics

Standard deviation0.049462247
Coefficient of variation (CV)5.0265384
Kurtosis326.91912
Mean0.0098402206
Median Absolute Deviation (MAD)0.0033832402
Skewness16.940341
Sum4.9201103
Variance0.0024465139
MonotonicityNot monotonic
2022-12-27T19:22:32.444493image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 165
33.0%
0.00625 2
 
0.4%
0.006071645416 1
 
0.2%
0.03071672355 1
 
0.2%
0.004385964912 1
 
0.2%
0.006420122246 1
 
0.2%
0.002669537137 1
 
0.2%
0.01632970451 1
 
0.2%
0.005588249839 1
 
0.2%
0.0007093456287 1
 
0.2%
Other values (325) 325
65.0%
ValueCountFrequency (%)
0 165
33.0%
0.0002705627706 1
 
0.2%
0.0005270092227 1
 
0.2%
0.0005415651232 1
 
0.2%
0.0005988920497 1
 
0.2%
0.0006635700066 1
 
0.2%
0.000687600275 1
 
0.2%
0.0007093456287 1
 
0.2%
0.0008802816901 1
 
0.2%
0.0009606147935 1
 
0.2%
ValueCountFrequency (%)
1 1
0.2%
0.3103448276 1
0.2%
0.25 1
0.2%
0.1666666667 1
0.2%
0.1333333333 1
0.2%
0.1094890511 1
0.2%
0.06086387435 1
0.2%
0.04958677686 1
0.2%
0.04724409449 1
0.2%
0.04601701469 1
0.2%

과실(%)
Real number (ℝ)

Distinct431
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.025468291
Minimum0
Maximum0.33333333
Zeros63
Zeros (%)12.6%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:32.539085image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.010605821
median0.020368473
Q30.03291987
95-th percentile0.062475392
Maximum0.33333333
Range0.33333333
Interquartile range (IQR)0.022314049

Descriptive statistics

Standard deviation0.026269144
Coefficient of variation (CV)1.0314451
Kurtosis40.429138
Mean0.025468291
Median Absolute Deviation (MAD)0.010981999
Skewness4.4947839
Sum12.734145
Variance0.00069006791
MonotonicityNot monotonic
2022-12-27T19:22:32.630845image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 63
 
12.6%
0.0303030303 3
 
0.6%
0.009615384615 2
 
0.4%
0.006896551724 2
 
0.4%
0.03290414878 2
 
0.4%
0.024 2
 
0.4%
0.007299270073 2
 
0.4%
0.02238966631 1
 
0.2%
0.01714964162 1
 
0.2%
0.02596926461 1
 
0.2%
Other values (421) 421
84.2%
ValueCountFrequency (%)
0 63
12.6%
0.002308935581 1
 
0.2%
0.003119800333 1
 
0.2%
0.004098360656 1
 
0.2%
0.004131377815 1
 
0.2%
0.004160887656 1
 
0.2%
0.004207426107 1
 
0.2%
0.004225352113 1
 
0.2%
0.004464285714 1
 
0.2%
0.004540295119 1
 
0.2%
ValueCountFrequency (%)
0.3333333333 1
0.2%
0.1469740634 1
0.2%
0.1453744493 1
0.2%
0.1373307544 1
0.2%
0.1300639659 1
0.2%
0.1261890895 1
0.2%
0.125 1
0.2%
0.1176470588 1
0.2%
0.09949409781 1
0.2%
0.09948169202 1
0.2%

생활용품(%)
Real number (ℝ)

Distinct437
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.039362267
Minimum0
Maximum1
Zeros59
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:32.729740image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.011509142
median0.027665226
Q30.045305045
95-th percentile0.084922282
Maximum1
Range1
Interquartile range (IQR)0.033795903

Descriptive statistics

Standard deviation0.080211991
Coefficient of variation (CV)2.0377889
Kurtosis96.095162
Mean0.039362267
Median Absolute Deviation (MAD)0.016319424
Skewness9.0109007
Sum19.681133
Variance0.0064339635
MonotonicityNot monotonic
2022-12-27T19:22:32.824086image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 59
 
11.8%
0.01041666667 2
 
0.4%
0.006993006993 2
 
0.4%
0.04347826087 2
 
0.4%
0.2105263158 2
 
0.4%
1 2
 
0.4%
0.01570082786 1
 
0.2%
0.01851851852 1
 
0.2%
0.01613879363 1
 
0.2%
0.03981009841 1
 
0.2%
Other values (427) 427
85.4%
ValueCountFrequency (%)
0 59
11.8%
0.001773364072 1
 
0.2%
0.0022172949 1
 
0.2%
0.002320185615 1
 
0.2%
0.002477700694 1
 
0.2%
0.002540327702 1
 
0.2%
0.002656042497 1
 
0.2%
0.002836879433 1
 
0.2%
0.003174603175 1
 
0.2%
0.003372681282 1
 
0.2%
ValueCountFrequency (%)
1 2
0.4%
0.7142857143 1
0.2%
0.6 1
0.2%
0.3333333333 1
0.2%
0.25 1
0.2%
0.2105263158 2
0.4%
0.1960784314 1
0.2%
0.1891891892 1
0.2%
0.1713221601 1
0.2%
0.1414141414 1
0.2%

서류(%)
Real number (ℝ)

Distinct426
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.016260261
Minimum0
Maximum0.15384615
Zeros68
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:32.917991image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0067515228
median0.013227346
Q30.020543174
95-th percentile0.0415297
Maximum0.15384615
Range0.15384615
Interquartile range (IQR)0.013791651

Descriptive statistics

Standard deviation0.016097869
Coefficient of variation (CV)0.99001292
Kurtosis16.248488
Mean0.016260261
Median Absolute Deviation (MAD)0.0066892557
Skewness3.0850292
Sum8.1301307
Variance0.00025914138
MonotonicityNot monotonic
2022-12-27T19:22:33.013788image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 68
 
13.6%
0.03278688525 2
 
0.4%
0.02631578947 2
 
0.4%
0.01180637544 2
 
0.4%
0.01041666667 2
 
0.4%
0.1052631579 2
 
0.4%
0.00625 2
 
0.4%
0.01614349776 2
 
0.4%
0.008095527221 1
 
0.2%
0.01365187713 1
 
0.2%
Other values (416) 416
83.2%
ValueCountFrequency (%)
0 68
13.6%
0.001421060111 1
 
0.2%
0.002103713054 1
 
0.2%
0.002392773823 1
 
0.2%
0.002477700694 1
 
0.2%
0.002580645161 1
 
0.2%
0.002836879433 1
 
0.2%
0.003022289384 1
 
0.2%
0.003174603175 1
 
0.2%
0.003343922421 1
 
0.2%
ValueCountFrequency (%)
0.1538461538 1
0.2%
0.1052631579 2
0.4%
0.09259259259 1
0.2%
0.08333333333 1
0.2%
0.07692307692 1
0.2%
0.07594936709 1
0.2%
0.07311827957 1
0.2%
0.07207207207 1
0.2%
0.06956521739 1
0.2%
0.06661115737 1
0.2%

수산(%)
Real number (ℝ)

Distinct472
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.072909174
Minimum0
Maximum0.8125
Zeros18
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:33.117231image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.013875489
Q10.048403393
median0.066350284
Q30.084235556
95-th percentile0.1340816
Maximum0.8125
Range0.8125
Interquartile range (IQR)0.035832162

Descriptive statistics

Standard deviation0.061257664
Coefficient of variation (CV)0.84019144
Kurtosis78.070552
Mean0.072909174
Median Absolute Deviation (MAD)0.017929819
Skewness7.2212368
Sum36.454587
Variance0.0037525014
MonotonicityNot monotonic
2022-12-27T19:22:33.213232image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18
 
3.6%
0.05263157895 3
 
0.6%
0.06666666667 3
 
0.6%
0.08333333333 3
 
0.6%
0.02380952381 2
 
0.4%
0.07407407407 2
 
0.4%
0.03448275862 2
 
0.4%
0.2019230769 2
 
0.4%
0.06060606061 2
 
0.4%
0.1862745098 1
 
0.2%
Other values (462) 462
92.4%
ValueCountFrequency (%)
0 18
3.6%
0.008547008547 1
 
0.2%
0.008810572687 1
 
0.2%
0.008849557522 1
 
0.2%
0.01049868766 1
 
0.2%
0.01162790698 1
 
0.2%
0.01265822785 1
 
0.2%
0.01362088536 1
 
0.2%
0.01388888889 1
 
0.2%
0.01445086705 1
 
0.2%
ValueCountFrequency (%)
0.8125 1
0.2%
0.7727272727 1
0.2%
0.4166666667 1
0.2%
0.3333333333 1
0.2%
0.2727272727 1
0.2%
0.2222222222 1
0.2%
0.2045152722 1
0.2%
0.2019230769 2
0.4%
0.1952277657 1
0.2%
0.1891891892 1
0.2%

양념/가루(%)
Real number (ℝ)

Distinct457
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.046012553
Minimum0
Maximum0.87692308
Zeros37
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:33.315010image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.029817059
median0.04177228
Q30.055001895
95-th percentile0.090944788
Maximum0.87692308
Range0.87692308
Interquartile range (IQR)0.025184836

Descriptive statistics

Standard deviation0.047364707
Coefficient of variation (CV)1.0293866
Kurtosis191.74659
Mean0.046012553
Median Absolute Deviation (MAD)0.012845657
Skewness11.441258
Sum23.006276
Variance0.0022434154
MonotonicityNot monotonic
2022-12-27T19:22:33.406753image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37
 
7.4%
0.04761904762 2
 
0.4%
0.05594405594 2
 
0.4%
0.01923076923 2
 
0.4%
0.03703703704 2
 
0.4%
0.04545454545 2
 
0.4%
0.02631578947 2
 
0.4%
0.02590673575 2
 
0.4%
0.02887044388 1
 
0.2%
0.01555209953 1
 
0.2%
Other values (447) 447
89.4%
ValueCountFrequency (%)
0 37
7.4%
0.005234231876 1
 
0.2%
0.006223743582 1
 
0.2%
0.006745362563 1
 
0.2%
0.00796812749 1
 
0.2%
0.008467400508 1
 
0.2%
0.008849557522 1
 
0.2%
0.008968609865 1
 
0.2%
0.009606147935 1
 
0.2%
0.01030927835 1
 
0.2%
ValueCountFrequency (%)
0.8769230769 1
0.2%
0.2865551425 1
0.2%
0.25 1
0.2%
0.1887763858 1
0.2%
0.1851851852 1
0.2%
0.1394668766 1
0.2%
0.1379310345 1
0.2%
0.1333333333 1
0.2%
0.1304347826 1
0.2%
0.1294642857 1
0.2%

음료(%)
Real number (ℝ)

Distinct439
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.043981066
Minimum0
Maximum0.43010753
Zeros60
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:33.502526image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.015515205
median0.036666121
Q30.062934906
95-th percentile0.10874811
Maximum0.43010753
Range0.43010753
Interquartile range (IQR)0.047419701

Descriptive statistics

Standard deviation0.042223467
Coefficient of variation (CV)0.96003737
Kurtosis16.656188
Mean0.043981066
Median Absolute Deviation (MAD)0.022739904
Skewness2.8108083
Sum21.990533
Variance0.0017828212
MonotonicityNot monotonic
2022-12-27T19:22:33.592735image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 60
 
12.0%
0.07142857143 2
 
0.4%
0.09090909091 2
 
0.4%
0.02624671916 1
 
0.2%
0.008866820358 1
 
0.2%
0.01851851852 1
 
0.2%
0.02622553964 1
 
0.2%
0.05924039192 1
 
0.2%
0.05701754386 1
 
0.2%
0.03921568627 1
 
0.2%
Other values (429) 429
85.8%
ValueCountFrequency (%)
0 60
12.0%
0.0004807692308 1
 
0.2%
0.0022172949 1
 
0.2%
0.002233389168 1
 
0.2%
0.002469135802 1
 
0.2%
0.002727024816 1
 
0.2%
0.002926115582 1
 
0.2%
0.003174603175 1
 
0.2%
0.003511118542 1
 
0.2%
0.00398142004 1
 
0.2%
ValueCountFrequency (%)
0.4301075269 1
0.2%
0.25 1
0.2%
0.2314814815 1
0.2%
0.2226269986 1
0.2%
0.2094240838 1
0.2%
0.204865557 1
0.2%
0.2024820379 1
0.2%
0.2 1
0.2%
0.1785714286 1
0.2%
0.1611792952 1
0.2%

잡곡(%)
Real number (ℝ)

Distinct392
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.011408338
Minimum0
Maximum0.1875
Zeros103
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:33.778241image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0026193683
median0.008191173
Q30.015099751
95-th percentile0.033701115
Maximum0.1875
Range0.1875
Interquartile range (IQR)0.012480382

Descriptive statistics

Standard deviation0.014134074
Coefficient of variation (CV)1.2389249
Kurtosis49.850219
Mean0.011408338
Median Absolute Deviation (MAD)0.0061676723
Skewness4.9656469
Sum5.7041692
Variance0.00019977206
MonotonicityNot monotonic
2022-12-27T19:22:33.872574image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 103
 
20.6%
0.01923076923 3
 
0.6%
0.01851851852 2
 
0.4%
0.01449275362 2
 
0.4%
0.02631578947 2
 
0.4%
0.004098360656 2
 
0.4%
0.008171603677 1
 
0.2%
0.006621420295 1
 
0.2%
0.006626173385 1
 
0.2%
0.004264392324 1
 
0.2%
Other values (382) 382
76.4%
ValueCountFrequency (%)
0 103
20.6%
0.0006811293124 1
 
0.2%
0.001126252956 1
 
0.2%
0.00122159785 1
 
0.2%
0.001509433962 1
 
0.2%
0.001586546089 1
 
0.2%
0.00167196121 1
 
0.2%
0.001705902422 1
 
0.2%
0.001726221302 1
 
0.2%
0.001739432945 1
 
0.2%
ValueCountFrequency (%)
0.1875 1
0.2%
0.08 1
0.2%
0.06988352745 1
0.2%
0.06944444444 1
0.2%
0.05882352941 1
0.2%
0.05510534846 1
0.2%
0.05263157895 1
0.2%
0.05208333333 1
0.2%
0.04777830865 1
0.2%
0.04545454545 1
0.2%

주곡(%)
Real number (ℝ)

Distinct386
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.012980517
Minimum0
Maximum0.22608696
Zeros109
Zeros (%)21.8%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:33.974387image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0025113929
median0.0090923975
Q30.016750434
95-th percentile0.036696137
Maximum0.22608696
Range0.22608696
Interquartile range (IQR)0.014239042

Descriptive statistics

Standard deviation0.018278177
Coefficient of variation (CV)1.408124
Kurtosis46.478005
Mean0.012980517
Median Absolute Deviation (MAD)0.007100739
Skewness5.309934
Sum6.4902586
Variance0.00033409177
MonotonicityNot monotonic
2022-12-27T19:22:34.066016image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 109
 
21.8%
0.005249343832 2
 
0.4%
0.06194690265 2
 
0.4%
0.004464285714 2
 
0.4%
0.01430615165 2
 
0.4%
0.03846153846 2
 
0.4%
0.03 2
 
0.4%
0.02360876897 1
 
0.2%
0.2260869565 1
 
0.2%
0.03888024883 1
 
0.2%
Other values (376) 376
75.2%
ValueCountFrequency (%)
0 109
21.8%
0.001001101211 1
 
0.2%
0.001296899114 1
 
0.2%
0.00133671969 1
 
0.2%
0.001421060111 1
 
0.2%
0.001689189189 1
 
0.2%
0.001792371666 1
 
0.2%
0.001793721973 1
 
0.2%
0.001795493312 1
 
0.2%
0.001897533207 1
 
0.2%
ValueCountFrequency (%)
0.2260869565 1
0.2%
0.1404958678 1
0.2%
0.1363636364 1
0.2%
0.09448818898 1
0.2%
0.09090909091 1
0.2%
0.08130081301 1
0.2%
0.07070707071 1
0.2%
0.06206896552 1
0.2%
0.06194690265 2
0.4%
0.05952380952 1
0.2%

채소(%)
Real number (ℝ)

Distinct484
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.24735008
Minimum0
Maximum0.6203365
Zeros9
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:34.160089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.07890625
Q10.18240787
median0.23931558
Q30.30392561
95-th percentile0.43873655
Maximum0.6203365
Range0.6203365
Interquartile range (IQR)0.12151773

Descriptive statistics

Standard deviation0.10383709
Coefficient of variation (CV)0.41979811
Kurtosis0.88598381
Mean0.24735008
Median Absolute Deviation (MAD)0.05949945
Skewness0.42614814
Sum123.67504
Variance0.010782142
MonotonicityNot monotonic
2022-12-27T19:22:34.250605image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
1.8%
0.1333333333 3
 
0.6%
0.2857142857 2
 
0.4%
0.119047619 2
 
0.4%
0.1666666667 2
 
0.4%
0.1176470588 2
 
0.4%
0.04545454545 2
 
0.4%
0.1621621622 2
 
0.4%
0.4903351658 1
 
0.2%
0.1821862348 1
 
0.2%
Other values (474) 474
94.8%
ValueCountFrequency (%)
0 9
1.8%
0.01716148962 1
 
0.2%
0.03076923077 1
 
0.2%
0.03448275862 1
 
0.2%
0.03631961259 1
 
0.2%
0.03846153846 1
 
0.2%
0.04545454545 2
 
0.4%
0.05333333333 1
 
0.2%
0.05555555556 1
 
0.2%
0.0612244898 1
 
0.2%
ValueCountFrequency (%)
0.6203365033 1
0.2%
0.6172839506 1
0.2%
0.5845256438 1
0.2%
0.5548387097 1
0.2%
0.5434714864 1
0.2%
0.5244040863 1
0.2%
0.5168160232 1
0.2%
0.5083088954 1
0.2%
0.5041322314 1
0.2%
0.5033259424 1
0.2%

축산물(%)
Real number (ℝ)

Distinct479
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.17997776
Minimum0
Maximum0.57506053
Zeros9
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:34.346892image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.07
Q10.13737903
median0.17318629
Q30.21589845
95-th percentile0.31431217
Maximum0.57506053
Range0.57506053
Interquartile range (IQR)0.078519422

Descriptive statistics

Standard deviation0.075564314
Coefficient of variation (CV)0.41985362
Kurtosis2.7392171
Mean0.17997776
Median Absolute Deviation (MAD)0.038351774
Skewness0.75993755
Sum89.988879
Variance0.0057099655
MonotonicityNot monotonic
2022-12-27T19:22:34.437158image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
1.8%
0.25 3
 
0.6%
0.21875 3
 
0.6%
0.1428571429 2
 
0.4%
0.1612903226 2
 
0.4%
0.1587301587 2
 
0.4%
0.08333333333 2
 
0.4%
0.1681415929 2
 
0.4%
0.1 2
 
0.4%
0.1621621622 2
 
0.4%
Other values (469) 471
94.2%
ValueCountFrequency (%)
0 9
1.8%
0.004777830865 1
 
0.2%
0.01290322581 1
 
0.2%
0.01652892562 1
 
0.2%
0.02323420074 1
 
0.2%
0.02912621359 1
 
0.2%
0.04545454545 1
 
0.2%
0.0462962963 1
 
0.2%
0.04962779156 1
 
0.2%
0.05224357114 1
 
0.2%
ValueCountFrequency (%)
0.5750605327 1
0.2%
0.5 1
0.2%
0.46 1
0.2%
0.4545454545 1
0.2%
0.4080944351 1
0.2%
0.3947368421 1
0.2%
0.3901734104 1
0.2%
0.3855799373 1
0.2%
0.3793103448 1
0.2%
0.376 1
0.2%

1회방문시평균구매금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41831.489
Minimum5766.0714
Maximum137791.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2022-12-27T19:22:34.531277image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum5766.0714
5-th percentile12973.922
Q126856.921
median37743.75
Q352597.026
95-th percentile84534.542
Maximum137791.36
Range132025.29
Interquartile range (IQR)25740.105

Descriptive statistics

Standard deviation22078.908
Coefficient of variation (CV)0.52780594
Kurtosis2.164173
Mean41831.489
Median Absolute Deviation (MAD)12563.243
Skewness1.1939322
Sum20915745
Variance4.8747819 × 108
MonotonicityNot monotonic
2022-12-27T19:22:34.631218image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23153.83721 1
 
0.2%
42032.46094 1
 
0.2%
32083.75 1
 
0.2%
47423.95062 1
 
0.2%
29571.36842 1
 
0.2%
18950 1
 
0.2%
13285.71429 1
 
0.2%
49890.74074 1
 
0.2%
70136.12426 1
 
0.2%
17662.63158 1
 
0.2%
Other values (490) 490
98.0%
ValueCountFrequency (%)
5766.071429 1
0.2%
5881.25 1
0.2%
6056.451613 1
0.2%
6100 1
0.2%
6265.555556 1
0.2%
6740 1
0.2%
6988.055556 1
0.2%
7675 1
0.2%
8166.666667 1
0.2%
8918.75 1
0.2%
ValueCountFrequency (%)
137791.3636 1
0.2%
129121.3529 1
0.2%
128427.2989 1
0.2%
125939.3718 1
0.2%
120904.2216 1
0.2%
116435.4902 1
0.2%
114989.6532 1
0.2%
110541.9822 1
0.2%
109110 1
0.2%
103435.9639 1
0.2%

Interactions

2022-12-27T19:22:28.652132image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:03.586558image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.058971image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.553176image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.916549image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.371082image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.778961image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.279391image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.812918image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.299241image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.790139image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:18.413512image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.977118image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.444047image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.800955image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.335209image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.774280image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.164629image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.730337image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:03.660763image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.133989image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.627024image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.991092image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.448517image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.857011image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.362141image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.893272image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.377702image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.872517image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:18.494211image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.052804image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.515925image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.878158image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.407255image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.848838image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.241667image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.811460image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:03.735393image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.210464image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.701041image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.064053image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.524251image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.938052image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.447057image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.971011image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.457725image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.958939image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:18.578257image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.133505image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.591114image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.959000image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.481369image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.923558image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.316948image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.890444image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:03.807636image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.284059image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.772615image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.135873image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.599090image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.012532image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.528790image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.046982image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.537304image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.045559image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:18.659476image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.210026image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.665100image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.035492image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.555417image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.996852image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.390949image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.966314image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:03.877756image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.356127image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.844512image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.206906image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.674948image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.181704image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.605933image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.121174image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.613003image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.124642image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:18.742460image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.282372image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.736459image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.206086image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.624142image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.070836image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.464783image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.049969image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:03.958450image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.436272image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.921061image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.283109image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.753673image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.259992image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.686461image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.205177image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.692810image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.208486image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:18.830453image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.359550image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.815015image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.286811image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.704175image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.149743image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.544321image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.130409image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.033342image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.511944image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.994115image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.356325image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.830040image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.335267image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.763896image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.282055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.766653image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.289837image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:18.916610image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.435035image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.887943image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.363883image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.776622image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.225764image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.619877image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.209827image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.197787image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.589410image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.068696image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.428492image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.906734image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.408480image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.840356image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.367397image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.840875image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.370148image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.006500image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.509931image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.960274image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.441844image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.848261image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.301140image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.791433image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.295055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.275220image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.671752image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.146668image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.507526image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.986374image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.486787image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.922294image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.455640image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.017687image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.454928image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.096412image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.589705image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.038460image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.526461image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.925824image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.380382image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.871159image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.375233image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.348923image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.745612image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.220641image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.581114image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.063043image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.561803image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.002265image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.534996image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.092076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.534602image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.185280image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.662785image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.110896image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.603758image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.997937image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.456989image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.947506image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.461796image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.431191image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.828094image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.303274image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.662848image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.147945image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.643144image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.085208image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.623024image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.173537image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.621831image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.278977image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.837767image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.192318image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.691559image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.079111image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.540706image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.029749image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.549692image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.513172image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.911513image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.386524image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.744474image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.231315image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.724304image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.166946image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.713190image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.254274image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.709291image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.375040image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.918285image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.274323image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.776589image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.159726image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.622769image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.112648image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.628468image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.586082image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:05.985901image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.459378image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.921636image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.305804image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.798537image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.238807image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.792382image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.326333image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.789668image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.458557image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:20.988630image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.344555image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.852478image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.229801image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.696238image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.186795image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.704884image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.657151image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.057807image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.532119image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:08.992808image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.380822image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.872812image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.313887image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.874463image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.401358image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.872512image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.545169image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.059905image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.414107image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:23.928862image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.301786image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.771215image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.259373image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.790681image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.739019image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.140204image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.611122image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.070623image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.462369image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:11.952816image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.398802image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:14.964063image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.481573image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:17.962953image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.638538image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.141393image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.494419image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.014365image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.380882image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.851431image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.339837image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.870155image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.814889image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.212679image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.683920image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.140187image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.535984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.030113image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.568911image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.042289image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.553829image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:18.046386image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.722990image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.212892image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.565705image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.089451image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.545753image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:26.924594image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.414298image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:29.951322image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.894271image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.288823image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.760921image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.217090image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.616842image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.108711image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.648884image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.127254image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.633149image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:18.132785image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.807291image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.287766image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.643033image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.169780image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.620964image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.004192image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.491895image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:30.129657image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:04.976249image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:06.367286image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:07.836853image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:09.292535image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:10.695941image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:12.193228image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:13.728623image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:15.212507image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:16.710103image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:18.218808image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:19.889828image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:21.365482image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:22.721704image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:24.252075image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:25.695617image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:27.082771image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-12-27T19:22:28.569146image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-12-27T19:22:34.728142image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Unnamed: 0회원번호구매금액(clean)구매수량(clean)총방문횟수간식(%)건강(%)과실(%)생활용품(%)서류(%)수산(%)양념/가루(%)음료(%)잡곡(%)주곡(%)채소(%)축산물(%)1회방문시평균구매금액회원상태성별결혼유무
Unnamed: 01.0001.000-0.097-0.078-0.0860.106-0.019-0.118-0.0040.027-0.0640.0260.131-0.072-0.059-0.143-0.044-0.0650.0000.0910.463
회원번호1.0001.000-0.097-0.078-0.0860.106-0.019-0.118-0.0040.027-0.0640.0260.131-0.072-0.059-0.143-0.044-0.0650.0000.0720.454
구매금액(clean)-0.097-0.0971.0000.9900.9420.1800.4510.3070.2600.1490.1210.1430.3110.2350.2690.1540.1390.7470.1800.1670.000
구매수량(clean)-0.078-0.0780.9901.0000.9590.2050.4240.2610.2490.1570.1010.1250.3320.2120.2390.1570.1110.6940.1410.1670.121
총방문횟수-0.086-0.0860.9420.9591.0000.1790.4170.2020.2350.1640.0750.0850.3080.2090.2220.1480.1410.5220.0770.1870.153
간식(%)0.1060.1060.1800.2050.1791.0000.1260.0260.212-0.031-0.1650.0730.340-0.068-0.031-0.400-0.1290.1490.0000.0810.119
건강(%)-0.019-0.0190.4510.4240.4170.1261.0000.0610.166-0.0130.0650.2040.3170.0470.053-0.1220.0940.3690.0000.2700.010
과실(%)-0.118-0.1180.3070.2610.2020.0260.0611.000-0.0470.1470.0240.039-0.0830.2240.3060.2720.0010.3260.0000.0250.082
생활용품(%)-0.004-0.0040.2600.2490.2350.2120.166-0.0471.000-0.049-0.0370.0470.251-0.0220.055-0.179-0.0540.2390.2390.0000.027
서류(%)0.0270.0270.1490.1570.164-0.031-0.0130.147-0.0491.0000.0700.003-0.0060.1620.1690.2440.0690.0430.0000.0490.103
수산(%)-0.064-0.0640.1210.1010.075-0.1650.0650.024-0.0370.0701.0000.149-0.0290.1570.1040.052-0.0550.1440.0000.0000.108
양념/가루(%)0.0260.0260.1430.1250.0850.0730.2040.0390.0470.0030.1491.0000.0820.0730.047-0.146-0.0550.1630.0000.0480.000
음료(%)0.1310.1310.3110.3320.3080.3400.317-0.0830.251-0.006-0.0290.0821.000-0.0670.015-0.2970.0430.2220.0000.1680.000
잡곡(%)-0.072-0.0720.2350.2120.209-0.0680.0470.224-0.0220.1620.1570.073-0.0671.0000.2700.207-0.0440.1610.0000.1580.048
주곡(%)-0.059-0.0590.2690.2390.222-0.0310.0530.3060.0550.1690.1040.0470.0150.2701.0000.1140.0620.2190.0000.1290.051
채소(%)-0.143-0.1430.1540.1570.148-0.400-0.1220.272-0.1790.2440.052-0.146-0.2970.2070.1141.000-0.1520.0350.0120.0490.130
축산물(%)-0.044-0.0440.1390.1110.141-0.1290.0940.001-0.0540.069-0.055-0.0550.043-0.0440.062-0.1521.0000.0620.0000.2210.115
1회방문시평균구매금액-0.065-0.0650.7470.6940.5220.1490.3690.3260.2390.0430.1440.1630.2220.1610.2190.0350.0621.0000.1480.1780.095
회원상태0.0000.0000.1800.1410.0770.0000.0000.0000.2390.0000.0000.0000.0000.0000.0000.0120.0000.1481.0000.0000.000
성별0.0910.0720.1670.1670.1870.0810.2700.0250.0000.0490.0000.0480.1680.1580.1290.0490.2210.1780.0001.0000.000
결혼유무0.4630.4540.0000.1210.1530.1190.0100.0820.0270.1030.1080.0000.0000.0480.0510.1300.1150.0950.0000.0001.000

Missing values

2022-12-27T19:22:30.264401image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-12-27T19:22:30.460352image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-12-27T19:22:30.581233image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Unnamed: 0회원번호회원상태성별결혼유무구매금액(clean)구매수량(clean)총방문횟수간식(%)건강(%)과실(%)생활용품(%)서류(%)수산(%)양념/가루(%)음료(%)잡곡(%)주곡(%)채소(%)축산물(%)1회방문시평균구매금액
002101정상회원기혼1991230.0381.00860.0787400.0472440.0078740.0209970.0157480.0104990.0393700.0262470.0131230.0052490.3097110.24934423153.837209
112102정상회원NaN2093160.0472.50790.3153440.0000000.0624340.0063490.0232800.0507940.0359790.0148150.0105820.0338620.2201060.10793726495.696203
222103정상회원기혼8273550.01675.401260.1693330.0105650.0280530.0352150.0125340.0943060.0370060.0411840.0083560.0071620.2799330.14742765663.095238
332104정상회원NaN6289495.01401.801250.1655010.0022830.0385220.0185480.0121270.0848910.0420890.0253960.0092740.0114140.2917680.15480150315.960000
442105정상회원기혼3067930.0602.00570.1478410.0199340.0514950.0149500.0249170.0481730.0415280.0581400.0232560.0099670.2724250.16113053823.333333
552106정상회원NaN3662240.0684.10770.0805440.0087710.0394680.0000000.0160800.0453150.0526240.0102320.0146180.0306970.4604590.14471647561.558442
662107정상회원기혼7161860.01419.751430.1169220.0000000.0348650.0331040.0056350.0869870.0429650.0142630.0218350.0112700.4349360.12396550082.937063
772108정상회원NaN6858020.01012.00870.1709490.0029640.0405140.0118580.0098810.0533600.0345850.0306320.0098810.0039530.3241110.20256978827.816092
882109정상회원NaN5230890.01028.901120.1334430.0175920.0665760.0476240.0136070.0456800.0553990.0427640.0077750.0136070.3839050.09913546704.375000
992110정상회원기혼5549725.01204.101450.2274730.0033220.0270820.0166100.0124570.0751600.0132880.0615400.0058130.0124570.2458180.20928538273.965517
Unnamed: 0회원번호회원상태성별결혼유무구매금액(clean)구매수량(clean)총방문횟수간식(%)건강(%)과실(%)생활용품(%)서류(%)수산(%)양념/가루(%)음료(%)잡곡(%)주곡(%)채소(%)축산물(%)1회방문시평균구매금액
4904902648정상회원NaN139700.016.040.0000000.0000000.0000000.0000000.0000000.8125000.0000000.0000000.1875000.0000000.0000000.00000034925.000000
4914912649정상회원기혼979800.0193.0390.4455960.0051810.0103630.0000000.0051810.0569950.0259070.0155440.0000000.0000000.1813470.16580325123.076923
4924922650정상회원기혼1150210.0233.5360.0985010.0000000.0364030.0128480.0085650.0513920.0299790.0556750.0256960.0042830.2655250.20985031950.277778
4934932651정상회원기혼1651310.0400.5590.0724090.0000000.0137330.0224720.0074910.0998750.0424470.0274660.0399500.0224720.4719100.10237227988.305085
4944942652정상회원미혼1270200.0209.3130.1638800.0000000.0860010.0573340.0047780.1051120.0621120.0238890.0477780.0191110.2293360.00477897707.692308
4954952653정상회원NaN3370870.0753.0730.0478090.0000000.0119520.0026560.0079680.2045150.0345290.0000000.0079680.0026560.4276230.12085046176.301370
4964962655정상회원NaN4512115.01108.81230.1379870.0002710.0081170.0216450.0108230.0649350.0387810.0532110.0018040.0126260.2538780.18308136683.861789
4974972656정상회원NaN562850.0137.0150.2189780.0000000.0072990.1386860.0000000.0364960.0291970.0364960.0000000.0000000.3795620.07299337523.333333
4984982659정상회원기혼1603280.0276.5430.1229660.0000000.0524410.0723330.0144670.0470160.0361660.0072330.0000000.0036170.4629290.15551537285.581395
4994992660정상회원NaN62900.07.020.1428570.0000000.0000000.7142860.0000000.0000000.0000000.0000000.0000000.0000000.0000000.14285731450.000000